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Queen Elizabeth II will learn about NASA education tomorrow, May 8, when she visits NASA's Goddard Space Flight Center in Greenbelt, Md. Bonnie Eisenhamer, the Hubble Space Telescope Formal Education Manager at the Space Telescope Science Institute in Baltimore, Md., will lead an education workshop for local middle school students during the Queen's Goddard visit. This tapestry of galaxies represents a small piece of the Hubble Ultra Deep Field (HUDF). Imaged September 2003 through January 2004, the HUDF is the deepest visible-light view of the cosmos. This snapshot includes galaxies of various ages, sizes, shapes, and colors. During the workshop, students will use the image to classify the galaxies in the HUDF by shape and color. By analyzing the HUDF image, the students will learn how light is used to explore the universe.

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      This workshop focused on the achievements of the SWOT EAs, offering a platform to share their projects with the community as they transition from “early adoption” to simply “adoption” of SWOT as a valuable resource in their system management toolbox. In addition, the meeting provided a space for discussions, an increased community awareness of the gaps and challenges of incorporating SWOT data into operational and decision-support framework for models, modeling systems, and other operational uses. Feedback from these discussions – especially concerning the known limitations of SWOT data with respect to data latency and mission length – will be exceptionally useful to the SWOT Project and Applications Teams.
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      Daniel Moreira [Brazil Geological Society (BGS)—Project Investigator] explained that the current gauge network on rivers across the Amazon basin is limited. SWOT data offers unprecedented spatial and temporal coverage of water storage processes and may be beneficial to prepare for floods and extreme events in the basin. Moreira’s group has compared several sites using Global Navigation Satellite System data and a gauge station elevation time series with very good results. In addition, BGS maintains a weekly water level report and a web application that leverages satellite altimetry data from the S6MF and Jason-3 missions for comparison across the Amazon Basin. BGS plans to produce discharge datasets over the Amazon using altimetry.
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      Robert Dudley [U.S. Geological Survey (USGS)] presented a project that involved the team integrating data from SWOT and in situ sources together to derive discharge and flow velocity for the Tanana and Yukon Rivers in Alaska. The USGS is collaborating with the Physical Oceanography Distributed Active Archive (PO.DAAC) to integrate SWOT in SatRSQ measurements to develop the Water Information from Space (WISP) dashboard to access time series of SWOT hydrology products. WISP is in development and not yet publicly available. When operational, it will enable comparisons with collocated, ground-gauged time series. WISP contains SWOT orbital ground tracks and will add the SWOT lake database in the future. The dashboard should be publicly available later in 2024.
      Gregg Jacobs [U.S. Naval Research Laboratory (NRL)] explained how NRL has evaluated SWOT KaRIn SSH data accuracy and integrated it into ocean forecast models by characterizing along-track errors in early data products to determine the necessary corrections. Jacobs then explained how the team computed daily interpolation of nadir altimeter data at SWOT crossover locations. They found good agreement between the corrected SWOT estimates and interpolated SSH from nadir altimeters and conducted ocean forecast experiments on California SWOT crossover Cal/Val sites – see Figure 2. NRL has had success in assimilating KaRIn data at a resolution of 5 km (~3 mi).
      Figure 2. Altimetry data collected over calibration/validation (Cal/Val) sites using traditional nadir altimeter data only [left], a combination of traditional nadir altimeter data and in situ observations [center], and a combination of traditional altimeter data and SWOT altimeter data. The dotted lines indicate the satellite ground track paths. Figure credit: U.S. Naval Research Laboratory Pierre Yves Le Traon [Mercator Ocean International (MOi)] explained that MOi is a non-profit that is now transforming into an intergovernmental organization. He began with a description of the Copernicus Marine Service, which is a long-term partnership between CNES, MOi, and a French company called Collecte Localisation Satellites (CLS) that focuses on ocean monitoring and forecasting. SWOT data will be used to constrain small scales in models – see Figure 3. The preliminary results are in good agreement with CNES Level-3 (L3) products. SWOT KaRIn data will be integrated into the operational Copernicus Marine Service operational forecast portfolio in 2025.
      Figure 3. Both these maps show the root mean square (RMS) error in the SWOT 21-day phase data in sea level anomaly (SLA) over one month on the 1/12° Mercator Ocean global forecasting system  The image pair contrasts the SLA RMS error without including SWOT data in the assimilation [left] versus when SWOT data are included in the assimilation [right]. Note that including SWOT data make smaller scale errors in the data become more apparent. Figure credit: Mercator Ocean International Guy Schumann [Water in Sight]explained this Swedish start-up company uses SWOT data to validate in situ gauge data in Malawi. Gauge readers and observers collect data at monitoring stations from south to north Malawi to support the government’s efforts in managing water and climate risks. They have used free Short Message Service and leveraged citizen science to develop a cloud platform for data access. For the next step, the project plans to integrate SWOT data into two-dimensional (2D) flood models. This EA project aims to address latency – time delay between collection and transmission of data – and interoperability challenges, enhancing hydrological network optimization as well as demonstrating the diverse complementary value of satellite observations. The group supports codesigned joint explorations, engagement activities, and technology alignment. The CNES hydroweb tool may be very useful in this endeavor, but Schumann acknowledges that there are interoperability challenges that need to be overcome.
      Jerry Wegiel [NASA’s Goddard Space Flight Center] explained that the U.S. Air Force’s Weather Land Information System (LIS) is a software framework used by multiple agencies for simulating land/hydrology processes. The Global Hydrology Intelligence (GHI) system (rebranding of LIS) is a comprehensive framework for hydrologic analysis, forecasting, and projections across scales encompassing all aspects of water security and addressing significant hydro-intelligence gaps identified by the defense and national security communities. Integration of SWOT L2 products operationally into the LIS Hydrological Modeling and Analysis Platform (HyMAP) model is expected to improve the global hydrological model data analysis system, as well as improve extreme hydrological event monitoring, reduce forecasting uncertainty, and support water security conflicts.
      Alexandre de Amorim Teixeira and Alexandre Abdalla Araujo [both at Agência Nacional de Águas e Saneamento Básico (ANA), or Brazilian National Water and Sanitation Agency] began by explaining that the ANA hydrography datasets [e.g., Base Hidrográfica Ottocodificada (BHO)] and water atlases [e.g., Base Hidrográfica Atlas-Estudos (BHAE)] have been extended using information from the SWOT River Database (SWORD) river reaches, which are roughly 10 km (~6 mi) SWORD-specified sections of a river, in Brazil – see Figure 4. By incorporating SWORD data into the BHAE, over 400,000 reaches have been identified – compared to 20,000 identified previously using SWORD alone. The latest version (6.2) of BHO will combine SWORD and BHAE data increasing numbers exponentially to nearly 5.5 million. The ANA EA project will use SWOT data to support water resource management in Brazil. ANA is working in collaboration with University Brasilia to integrate available gauge information on rivers and reservoirs to fulfill their mandate to determine and report on water availability in the country. They described a sophisticated hexagonal hierarchical geospatial indexing system that will support hydrological and hydrodynamical modeling and cross-validation. The team will use SWOT data pixel cloud or raster products to best serve their needs.
      Figure 4. The Agência Nacional de Águas e Saneamento Básico’s (ANA) [Brazilian National Water and Sanitation Agency] SWOT Early Adopter project is extending hydrography datasets, e.g., Base Hidrográfica Ottocodificada (BHO) [top] and water atlases, e.g., Base Hidrográfica Atlas-Estudos (BHAE) [middle] using the SWOT data to produce the SWOT River Database (SWORD) product [bottom] that expands on the extent of the BHO hydrography dataset. Image credit: ANA Data Systems and Products for Early Adopters
      In 2021, the SWOT Project Science Team made simulated datasets available for select hydrologic and oceanographic regions. These datasets shared many characteristics in common with future SWOT data products (e.g., formats, metadata, and data contents) and were intended to familiarize users with the expected SWOT science data products.
      At this meeting, teams from both the NASA and CNES mission data system and data repositories shared timely and valuable information and updates with the EA community. The talks provided information and insight into what users can expect from SWOT products.
      Lionel Zawadzki and Cyril Germineaud [both at CNES] described the use of SWOT data available from CNES through the AVISO (ocean and coastal) and hydroweb.next (hydrology and ocean) data portals. Systems supporting data access include data acquisition and production, data repositories, and ultimately cloud data access through thematic portals.
      Catalina Taglialatela and Cassandra Nickles [both at JPL] discussed the use of KaRIn high-resolution and low-resolution SWOT data products available through PO.DAAC, which provides centralized, searchable access that is available using an in-cloud commercial web service through the NASA EarthData portal. The team demonstrated resources and tutorials available via the online PO.DAAC Cookbook: SWOT Chapter, as well as the new Hydrocron SWOT time series applications programming interface (API) for generating time series over water features identified in SWORD and SWODLR, which is a system for creating on-demand L2 SWOT raster products.
      Shailen Desai [JPL] explained how KaRIn products depend on upstream orbit, attitude, and radiometer products for optimal accuracy. SWOT KaRIn, nadir altimeter, and radiometer products are now in operational production and routinely available. Product description documents and SWOT algorithm theoretical basis documents are all publicly available.
      Curtis Chen [JPL] discussed how the SWOT science data system team have reduced complexities of the KaRIn measurements to ensure robust interpretation of the results. Knowledge of measurement details may be especially important in trying to interpret the pre-validated data products. During his presentation, Chen addressed practical aspects of interpreting KaRIn data products, including answers to frequently asked questions and tips to avoid confusion and misinterpretation in using the data.
      Yannice Faugere [CNES] explained how CNES will assimilate SWOT data into Mercator Ocean with value-added elements, including multimission calibration, noise mitigation, and images that blend KaRIn and nadir instruments. A preliminary assessment of L4 products was conducted using one-day Cal/Val orbit measurements with promising results. Tests on 21-day data and an L4 data challenge for community feedback to compare mapping and validation methods are in process.
      Complementary Projects
      Participants spoke about a number of other projects and programs during the meeting. The selected presentations address elements relevant to SWOT applications.
      Charon Birkett [NASA] discussed how SWOT data will be incorporated into the Global REservoir and LAke Monitor (G-REALM) and Global Water Measurements (GWM) portal, to integrate nadir radiometer and KaRIn measurements. G-REALM maintains a 30-plus-year time series of nadir altimeter data from the NASA/CNES reference missions for this measurement (i.e., Topex/Poseidon; Jason -1, -2, and -3; and S6MF) as well as the European Remote Sensing Satellite. GWM is focused on lakes and reservoirs, rivers, and wetland water levels to derive surface extents and storage change.
      Stephanie Granger [JPL] introduced the Western Water Applications Office (WWAO), which provides NASA data, technology, and tools for water management to water managers in the western U.S. The WWAO team completes needs assessments for basins – a task complicated by the more than 100 agencies involved in water management activities in the western U.S. Granger identified several activities that could benefit from SWOT data, such as extreme event predictions and impacts, timely streamflow predictions at a sub-basin level, wet/dry indicators from streamflow monitoring, and flood plain mapping.
      Babette Tchonang, Dimitris Menemenlis,and Matt Archer [all from JPL] presented a study that evaluates the feasibility of applying the Estimating the Circulation and Climate of the Ocean 4-Dimensional Variational (MITgcm-ECCO 4DVAR) data assimilation framework to a sub-mesoscale resolving model [grid resolution of 1 km (~0.6 mi)] in preparation for future studies to assimilate SSH measurements from SWOT. Two model solutions are nested within the global 1/12° Hybrid Coordinate Ocean Model (HYCOM)/Navy Coupled Ocean Data Assimilation (NCODA) analysis. Comparing the two model solutions against assimilated and withheld in situ observations indicates that the MITgcm-ECCO 4DVAR framework can be applied to the reconstruction of sub-mesoscale ocean variability. This data assimilation system is now being used by the Scripps Institution of Oceanography to support SWOT post-launch activities.
      Matt Bonnema [JPL] presented the Observational Products for End-Users from Remote Sensing Analysis (OPERA) project, which produces a suite of surface water extent products, such as Dynamic Surface Water extent (DSWx). The products are based on a variety of optical and radar sensors built on existing satellite data that are freely available from NASA. DSWx gives two dimensions of surface water measurements (i.e., spatial extent), whereas SWOT produces three dimensions of surface water measurement (i.e., spatial extent and elevation). DSWx has the potential to fill in temporal gaps in SWOT observations and to cross-compare DSWx and SWOT when observations are concurrent. DSWx is a valuable source of global water information that can be used to interpret and enhance SWOT’s capabilities.
      Renato Frasson [JPL] explained how the U.S. Army Corps of Engineers support the National Geospatial-Intelligence Agency (NGA), which uses water storage and lake/reservoir flux information primarily from NASA’s MODerate resolution Imaging Spectroradiometer (MODIS) that flies on both the Terra and Aqua platforms. SWOT data has a higher spatial resolution for river widths, and NASA–ISRO Synthetic Aperture Radar (NISAR) observations are planned to be incorporated into the OPERA platform.
      Cedric David [NASA/JPL] discussed how SWOT data can improve state-of-the-art hydrologic models to address environmental and societal challenges in river system science (e.g., flooding, water security, river biodiversity, changing deltas, and transboundary issues). Model advancements (e.g., U.S. National Water Model) can be realized in areas such as uncertainty quantification, data assimilation, bias correction, and decreasing numbers of in situ observation systems. Incorporating SWOT data into river models will lead to more realistic representations of these rivers, which in turn will improve the users’ ability to understand and effectively manage these critical and threatened water resources.
      Workshop Recommendations and Feedback
      This 2023 SWOT Applications Workshop provided an opportunity to share early experiences with SWOT data and insight into integration of the data into operational and decision-support workflows and models (e.g., ocean circulation and hydrologic, hydrodynamic, and decision support). Understanding how EAs integrate SWOT data and the associated challenges is critical to provide a clear analytical path for assessing the value of SWOT’s observations.
      Integrating satellite observations into models enhances the model’s capability to forecast natural phenomena and monitor remote or inaccessible regions, expanding modeling capabilities dynamically and spatially. The EA-user community shared information on the potential of incorporating SWOT data into local- or community-wide models or modeling systems. SWOT’s high-resolution data – particularly from the KaRIn instrument – can enhance the precision of hydrology and ocean models by enabling detailed simulations of water dynamics. This includes accurate mapping of freshwater bodies and SSH. Both these measurements are crucial for managing water resources, predicting floods, and understanding ocean circulation patterns. The incorporation of SWOT data into model systems enables significant advancement and insights that can inform environmental management policies and practices by supporting more informed decision-making.
      Although the SWOT nadir altimeter data products are being operationally produced and distributed through the data centers, the new data products from the novel KaRIn instrument continue to be assessed. An entire year of data is necessary for a more comprehensive assessment of value, ease of use, and degree to which SWOT data will impact operations and decision-making.
      Throughout the workshop, EAs shared their experiences and specific needs in regard to early use of SWOT data in their modeling frameworks. Overall impressions were positive, but the actual use of SWOT beta product data was limited to a few projects (e.g., NRL, Sofar Ocean, and Copernicus Marine Service). Overall, the meeting participants supported the need for lower-latency products.
      In the coming year, the impact of SWOT data with lower 21-day science orbital repeat frequency and latency on various applications will be understood further. Ultimately, the most important feedback from SWOT EAs is yet to come.
      SWOT has the potential to provide invaluable information to operational user communities through its ability to advance understanding of global surface water dynamics. The SWOT Applications Program has successfully engaged a diverse cohort of agencies and the commercial sector to support integrating SWOT data into operational workflows. Moving forward, the program aims to highlight societal benefits, support applied research in hydrology and oceanography, expand user engagement, and provide ongoing training to maximize the effective use of fully validated SWOT data products.
      Conclusion
      The 2023 SWOT Applications meeting was a successful and timely engagement opportunity, further strengthening the connection between the different collaborating organizations. Many EAs demonstrated early ingest of the preliminary release of KaRIn data, with some having already started using the nadir altimeter data in their operational processes. Engagement will continue as more data, including pre-validated and validated science products, become regularly available with support to the EA community.
      Future SWOT Application activities will include continued communication at community meetings and conferences as well as with a broader audience to engage new users for both applied research and operational activities through workshops, hackathons, and telecons. The SAWG will continue working with EAs and the applied and operational user communities to identify and apply value of SWOT to support decision makers and operational agencies.
      NASA and CNES data distribution centers will continue to train users in cloud data access, data formats, and preferred formats for different topics, as well as provide EA feedback to improve data products and platform services. NASA and CNES will continue to work with EAs to overcome technical hurdles, help complete their projects, and generate high-impact success stories, as well as expand the extent of SWOT EAs and applied science users to build recognition of SWOT among practitioners.
      Acknowledgment: The author wishes to acknowledge the contribution of Stacy Kish [NASA’s Goddard Space Flight Center (GSFC)/Global Science and Technology, Inc. (GST)] for her editing work to reduce/repurpose the full summary report to create a version suitable for the context of The Earth Observer.
      Margaret Srinivasan
      NASA/Jet Propulsion Laboratory, California Institute of Technology
      margaret.srinivasan@jpl.nasa.gov
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